Clinical and Biomarker Predictors of Expanded Heart Failure Outcomes in Patients With Type 2 Diabetes Mellitus After a Recent Acute Coronary Syndrome: Insights From the EXAMINE Trial
Bibliographic record
Abstract
Background Improved heart failure ( HF ) risk stratification after a recent acute coronary syndrome may identify those who can benefit from therapies that reduce HF risk. We aimed to identify clinical and biomarker predictors for expanded HF outcomes in patients with type 2 diabetes mellitus after recent acute coronary syndrome. Methods and Results The EXAMINE ( Ex amination of Cardiovascular Outcomes with Alogliptin versus Standard of Care) trial was a multicenter, non‐inferiority, double‐masked, placebo‐controlled study which randomized 5380 patients with type 2 diabetes mellitus after recent acute coronary syndrome to alogliptin or placebo. Baseline biomarkers were measured in 5154 patients: NT‐proBNP (N‐terminal pro‐B‐type natriuretic peptide), high‐sensitivity troponin I, adiponectin, growth‐differentiation‐factor‐15, and galectin‐3. Our primary outcome was cardiovascular) death, HF hospitalization, elevated NT‐proBNP during follow‐up, or loop diuretics initiation. The association between clinical variables, biomarkers, and outcomes were assessed using Cox regression models. In the study population, the median age was 61.0 years, 67.7% were men, and 28.0% had baseline HF (median follow‐up was 18 months). In multivariable analyses, NT‐proBNP had the strongest association with the primary outcome (per log 2 , hazard ratio 1.24; Wald χ 2 67.4; P <0.0001) followed by a prior HF history (hazard ratio 1.42; Wald χ 2 20.8; P <0.0001). A model with clinical variables and biomarkers allowed for risk prediction for expanded HF outcomes (C‐statistic=0.72). Discrimination results were similar for cardiovascular death or HF hospitalization. Conclusions Among patients with type 2 diabetes mellitus after recent acute coronary syndrome, the use biomarkers such as N‐terminal pro‐B‐type natriuretic peptide and clinical variables enables risk stratification for expanded HF outcomes. Clinical Trial Registration URL : https://www.clinicaltrials.gov/ . Unique identifier: NCT 00968708.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".